AI-Assisted Prompt Engineering Identifies KRT19 as a Genetically Validated Therapeutic Target

Abstract

Artificial intelligence–assisted prompting offers a transformative strategy for rapidly identifying and contextualizing biological targets. Using Swalife PromptStudio, we present a case study of Keratin 19 (KRT19) demonstrates strong genetic evidence linking it to disease risk, particularly in fibrotic disorders and cancer. Genome-wide association studies (GWAS) reveal three significant hits at the KRT19 locus, with complete replication across independent cohorts, underscoring the robustness of the association. The lead SNP for liver fibrosis shows a modest but meaningful effect size (OR = 1.28, 95% CI: 1.18–1.39). ClinVar and OMIM report no Mendelian disorders, but common variants highlight KRT19 as a contributor to complex disease. gnomAD analysis shows low loss-of-function constraint (pLI = 0.1), indicating tolerance to inhibition. Importantly, eQTL evidence links increased KRT19 expression to higher risk, supporting KRT19 inhibition as a genetically validated therapeutic strategy with favorable safety potential. This study highlights the effectiveness of AI-driven prompt engineering as a scalable and reproducible framework for precision target prioritization.